Comment on nhess-2021-200

doi:10.5194/nhess-2021-200-rc2

Abstract

Urbanization and climate change are the critical challenges in the 21st century. Flooding by extreme weather events and human activities can lead to catastrophic impacts in fast-urbanizing areas. However, high uncertainty in climate change and future urban growth limit the ability of cities to adapt to flood risk. This study presents a multi-scenario risk assessment method that couples the future land use simulation model (FLUS) and floodplain inundation model (LISFLOOD-FP) to simulate and evaluate the impacts of future urban growth scenarios with flooding under climate change (two representative concentration pathways (RCPs 2.6 and 8.5)). By taking Shanghai coastal city as an example, we then quantify the role of urban planning policies in future urban development to compare urban development under multiple policy scenarios (Business as usual, BU; Growth as planned, GP; Growth as eco-constraints, GE). Geospatial databases related to anthropogenic flood protection facilities, land subsidence, and storm surge are developed and used as inputs to the LISFLOOD-FP model to estimate flood risk under various urbanization and climate change scenarios. The results show that urban growth under the three scenario models manifests significant differences in expansion trajectories, influenced by key factors such as infrastructure development and policy constraints. Comparing the urban inundation results for the RCP2.6 and RCP8.5 scenarios, the urban inundation area under the GE scenario is less than that under the BU scenario, but more than that under the GP scenario. We also find that urban will tend to expand to areas vulnerable to floods under the restriction of ecological environment protection. The increasing flood risk information determined by the coupling model helps to understand the spatial distribution of future flood-prone urban areas and promote the re-formulation of urban planning in high-risk locations.

Highlights

Climate change and urbanization are the global challenges for the 21st century (Pecl et al, 2017; Ramaswami et al, 2016).Floods have been key threats for many cities around the world driven by global climate change (Fang et al, 2020; Hallegatte et al, 2013; Intergovernmental Panel on Climate Change (IPCC), 2014)
The results show that urban growth under the three scenario models manifests significant differences in expansion trajectories, influenced by key factors such as infrastructure development and policy constraints
The future land use simulation model (FLUS) model improves the simulation accuracy of the model by combining artificial neural network (ANN) and Cellular automata (CA) model to simulate nonlinear land use changes while considering parameters related to environment, society, climate change, etc. (Liu et al, 2017; Zhai et al, 2020)

Summary

Introduction

Climate change and urbanization are the global challenges for the 21st century (Pecl et al, 2017; Ramaswami et al, 2016). Floods have been key threats for many cities around the world driven by global climate change (Fang et al, 2020; Hallegatte et al, 2013; IPCC, 2014). The United Nations reports that the global population will increase by 29% (7.6 billion) between 2017 and 2050 (United Nations, 2017b), which means that population of coastal cities will become increasingly concentrated in the future and impervious surfaces will become more numerous (Chen et al, 2020). The National Oceanic and Atmospheric Administration (NOAA) report suggests that global mean sea level will rise around 0.2 m to 2.0 m by 2100 under a continuing global warming trend (Parris et al, 2012). Properties and populations in many coastal areas will suffer more severely in the future if the effects of land subsidence are taken into account (Vousdoukas et al, 2018)

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Conclusion